<i>In Silico</i> Modeling of Immunotherapy and Stroma-Targeting Therapies in Human Colorectal Cancer

Kather, Jakob Nikolas; Poleszczuk, Jan; Suarez-Carmona, Meggy; Krisam, Johannes; Charoentong, Pornpimol; Valous, Nektarios A.; Weis, Cleo–Aron; Tavernar, Luca; Leiß, Florian; Herpel, Esther; Klupp, Fee; Ulrich, Alexis; Schneider, Martin; Marx, Alexander; Jäger, Dirk; Halama, Niels

doi:10.1158/0008-5472.can-17-2006

Cited by 92 publications

(78 citation statements)

References 56 publications

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“…In the iTME, T cells and macrophages are among the most abundant immune cells and are closely related to clinical outcome (Fridman et al, 2012;Fridman et al, 2017;Kather et al, 2017;Kather et al, 2018). This was supported by analysis of our CRC cohort, which identified T cell-and macrophage-enriched CNs.…”

Section: Discussionsupporting

confidence: 61%

“…Naturally, the question arises as to how a tumor avoids immune action, such as by T cell exclusion (Joyce and Fearon, 2015) or the increased prevalence of certain cell types, including Tregs, macrophages and myeloidderived suppressor cells (Gajewski et al, 2013;Hanahan and Weinberg, 2011;Kumar et al, 2016;Munn and Bronte, 2016). Several recent studies have characterized tumor-immune phenotypes in detail, but how spatial organization and the associated crosstalk between iTME components determine the effectiveness of the antitumoral immune responses has not yet been determined (Kather et al, 2017;Kather et al, 2018;Newell and Becht, 2018).…”

Section: Discussionmentioning

confidence: 99%

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Coordinated cellular neighborhoods orchestrate antitumoral immunity at the colorectal cancer invasive front

Schürch

Bhate

Barlow

et al. 2019

Preprint

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Antitumoral immunity requires organized, spatially nuanced interactions between components of the immune tumor microenvironment (iTME). Understanding this coordinated behavior in effective versus ineffective tumor control will advance immunotherapies. We optimized CO-Detection by indEXing (CODEX) for paraffin-embedded tissue microarrays, enabling profiling of 140 tissue regions from 35 advanced-stage colorectal cancer (CRC) patients with 56 protein markers simultaneously. We identified nine conserved, distinct cellular neighborhoods (CNs)-a collection of components characteristic of the CRC iTME. Enrichment of PD-1 + CD4 + T cells only within a granulocyte CN positively correlated with survival in a high-risk patient subset. Coupling of tumor and immune CNs, fragmentation of T cell and macrophage CNs, and disruption of inter-CN communication was associated with inferioroutcomes. This study provides a framework for interrogating complex biological processes, such as antitumoral immunity, demonstrating an example of how tumors can disrupt immune functionality through interference in the concerted action of cells and spatial domains.

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Section: Discussionsupporting

confidence: 61%

Section: Discussionmentioning

confidence: 99%

Coordinated cellular neighborhoods orchestrate antitumoral immunity at the colorectal cancer invasive front

Schürch

Bhate

Barlow

et al. 2019

Preprint

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“…Our third case corresponds to a glandular tumour that grows by invading normal tissue. To parameterize this model, we estimated the number of cells per gland in well-differentiated adenocarcinomas -one of the most abundant types of human cancer across primary sites -using semi-automated analysis of histopathological slides selected at random for three patients with advanced colorectal cancer, a tumour type with pronounced stromal infiltration and spatially separated glands [16]. We delineated a total of 41 clearly separated glands in whole-slide images from the three patients and counted the cells in each gland with digital pathology software [17] (Supplementary figure 1).…”

Section: Variation In Tumour Evolutionary Modementioning

confidence: 99%

Spatial structure governs the mode of tumour evolution

Noble

Burri

Kather

et al. 2019

Preprint

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Characterizing the mode -the way, manner, or pattern -of evolution in tumours is important for clinical forecasting and optimizing cancer treatment. DNA sequencing studies have inferred various modes, including branching, punctuated and neutral evolution, but it is unclear why a particular pattern predominates in any given tumour [1]. Here we propose that differences in tumour architecture alone can explain the variety of observed patterns. We examine this hypothesis using spatially explicit population genetic models and demonstrate that, within biologically relevant parameter ranges, tumours are expected to exhibit diverse evolutionary modes including four archetypal "oncoevotypes": rapid clonal expansion (predicted in leukaemia); progressive diversification (in colorectal adenomas and early-stage colorectal carcinomas); branching evolution (in invasive glandular tumours); and almost neutral evolution (in certain non-glandular and poorly differentiated solid tumours). We thus provide a simple, mechanistic explanation for a wide range of empirical observations. Oncoevotypes are driven by differences in cell dispersal and cell-cell interactions, which we show are essential for accurately characterizing, forecasting and controlling tumour evolution.A tumour is a product of somatic evolution in which interacting processes of mutation, selection, genetic drift, and cell dispersal generate a patchwork of cell subpopulations (clones) with varying degrees of aggressiveness and treatment sensitivity [2]. A primary goal of modern cancer research is to characterize this evolutionary process, so as to enable precise, patient-specific prognostic forecasts and to optimize targeted therapy regimens.Much progress has been made in revealing the evolutionary features of particular cancers, yet these findings raise as many questions as they answer. Why do different tumour types exhibit different modes of evolution [1,3,4,5,6]? What conditions sustain the frequently observed pattern of branching evolution, in which several clones diverge and evolve in parallel [1,7]? And why do some pan-cancer analyses indicate that many tumours evolve neutrally [8], whereas others support extensive selection [9]?Factors proposed as contributing to intra-tumour evolution include microenvironmental heterogeneity, niche construction, and positive ecological interactions between clones [10, 2]. However, because such factors have not been well characterized across human cancer types, it remains unclear how they might relate to evolutionary modes.On the other hand, it is well established that tumours exhibit a wide range of architectures. In leukaemia, for example, mutated stem cells in semi-solid bone marrow produce cancer cells that mix and proliferate in the bloodstream (Figure 1a). Colorectal adenomas and early-stage colorectal carcinomas, by contrast, inherit 1

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“…Several ABM have simulated the immune system's involvement in maintaining homeostasis and disease conditions, such as bacterial infections [59], fungal infections [60], abnormal systemic inflammatory response [61], ulceration [62], allergens [63], ischemia [64], tuberculosis [65], sepsis [66], and wound healing [67]. For cancers, such models include tumor growth and invasion [68], as well as specific cancer types such as hepatocellular carcinoma [69], breast cancer [70], melanoma [71], colorectal [72], lung cancer [73,74], and metastasis [75]. Software packages have been developed based on the ABM framework to study the immune system; these include ImmSim [76][77][78][79], Immunogrid [80,81], Simmune [82], Cycell [83], and PhysiCell [84].…”

Section: Overview Of Computational Modeling Methodologies Including Amentioning

confidence: 99%

“…Kather et al used ABM to investigate the combination of adoptive cell transfer and therapy that permeabilized the fibrotic stromal component in colorectal cancer [72]. Adoptive cell transfer is a therapeutic strategy that aims to increase the number of immune cells to strengthen immuno-surveillance and counter tumor development.…”

Section: Overview Of Computational Modeling Methodologies Including Amentioning

confidence: 99%

Multiscale Agent-Based and Hybrid Modeling of the Tumor Immune Microenvironment

et al. 2019

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Multiscale systems biology and systems pharmacology are powerful methodologies that are playing increasingly important roles in understanding the fundamental mechanisms of biological phenomena and in clinical applications. In this review, we summarize the state of the art in the applications of agent-based models (ABM) and hybrid modeling to the tumor immune microenvironment and cancer immune response, including immunotherapy. Heterogeneity is a hallmark of cancer; tumor heterogeneity at the molecular, cellular, and tissue scales is a major determinant of metastasis, drug resistance, and low response rate to molecular targeted therapies and immunotherapies. Agent-based modeling is an effective methodology to obtain and understand quantitative characteristics of these processes and to propose clinical solutions aimed at overcoming the current obstacles in cancer treatment. We review models focusing on intra-tumor heterogeneity, particularly on interactions between cancer cells and stromal cells, including immune cells, the role of tumor-associated vasculature in the immune response, immune-related tumor mechanobiology, and cancer immunotherapy. We discuss the role of digital pathology in parameterizing and validating spatial computational models and potential applications to therapeutics.

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In Silico Modeling of Immunotherapy and Stroma-Targeting Therapies in Human Colorectal Cancer

Cited by 92 publications

References 56 publications

Coordinated cellular neighborhoods orchestrate antitumoral immunity at the colorectal cancer invasive front

Coordinated cellular neighborhoods orchestrate antitumoral immunity at the colorectal cancer invasive front

Spatial structure governs the mode of tumour evolution

Multiscale Agent-Based and Hybrid Modeling of the Tumor Immune Microenvironment

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